Sequencing of the genomes of several species (including humans) opens the door to a new understanding of biological function, as well as to the possible elucidation of the genetic mechanisms of many diseases, and perhaps to their cure through genetic manipulation. This research aims at improving current computational methods that predict the three dimensional structure of proteins from the knowledge of their aminoacid sequence. Protein function is more closely related to structure than to sequence, and hence methodologies that can produce large scale predictions of protein structure are essential in this post-genomic era. Reduced, lattice based models of proteins, and Monte Carlo simulation methods will be used to analyze the mechanisms of ab initio protein folding, and the relationship between sequence and characteristic structural motifs of the folded protein. Statistical methods to detect long ranged structural correlations will be incorporated to existing algorithms of protein structure prediction in order to increase sensitivity in the detection of functional sites.